Instructions to use nathanReitinger/FASHION-vision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nathanReitinger/FASHION-vision with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nathanReitinger/FASHION-vision") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("nathanReitinger/FASHION-vision") model = AutoModelForImageClassification.from_pretrained("nathanReitinger/FASHION-vision", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download scheduler.pt from nathanReitinger/FASHION-vision: direct link, hf CLI and curl.
- Browser
- Download file 1.06 kB
-
https://huggingface.co/nathanReitinger/FASHION-vision/resolve/main/scheduler.pt
- Command line
-
hf download hf://nathanReitinger/FASHION-vision/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/nathanReitinger/FASHION-vision/resolve/main/scheduler.pt
1.06 kB
- Xet hash:
- 0eb75886bcf00cf93192d79a0441688a8ac21157f08086942d9a8b43d85238a9
- Size of remote file:
- 1.06 kB
- SHA256:
- fc73d79f7cd69156b9b62487f22f2c189114952753fb3c71e91e094a76b5f22e
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